// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "kernels/funcs/npu_funcs.h"
#include "kernels/funcs/npu_op_runner.h"

namespace custom_kernel {

template <typename T, typename Context>
static void BatchMatMul(const Context& dev_ctx,
                        const aclrtStream& stream,
                        const phi::DenseTensor& x,
                        const phi::DenseTensor& y,
                        const bool transpose_x,
                        const bool transpose_y,
                        phi::DenseTensor* out) {
  dev_ctx.template Alloc<T>(out);
  const auto& runner =
      NpuOpRunner("BatchMatMul",
                  {x, y},
                  {*out},
                  {{"adj_x1", transpose_x}, {"adj_x2", transpose_y}});
  runner.Run(stream);
}

template <typename T, typename Context>
void BmmKernel(const Context& dev_ctx,
               const phi::DenseTensor& x,
               const phi::DenseTensor& y,
               phi::DenseTensor* out) {
  auto stream = dev_ctx.stream();
  BatchMatMul<T>(dev_ctx, stream, x, y, false, false, out);
}

template <typename T, typename Context>
void BmmGradKernel(const Context& dev_ctx,
                   const phi::DenseTensor& x,
                   const phi::DenseTensor& y,
                   const phi::DenseTensor& dout,
                   phi::DenseTensor* dx,
                   phi::DenseTensor* dy) {
  auto stream = dev_ctx.stream();
  if (dx) {
    BatchMatMul<T>(dev_ctx, stream, dout, y, false, true, dx);
  }
  if (dy) {
    BatchMatMul<T>(dev_ctx, stream, x, dout, true, false, dy);
  }
}

}  // namespace custom_kernel

PD_REGISTER_PLUGIN_KERNEL(bmm,
                          npu,
                          ALL_LAYOUT,
                          custom_kernel::BmmKernel,
                          float,
                          phi::dtype::float16) {}

PD_REGISTER_PLUGIN_KERNEL(bmm_grad,
                          npu,
                          ALL_LAYOUT,
                          custom_kernel::BmmGradKernel,
                          float,
                          phi::dtype::float16) {}
